Impact of urban aerosols on the cloud condensation activity using a clustering model
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Rejano Martínez, Fernando; Casquero Vera, Juan Andrés; Casans Gabasa, Andrea; Pérez Ramírez, Daniel; Alados Arboledas, Lucas; Titos Vela, Gloria; Olmo Reyes, Francisco JoséEditorial
Elsevier
Materia
Activation properties CCN Particle size distribution K-means clustering
Date
2022-10-25Referencia bibliográfica
Fernando Rejano... [et al.]. Impact of urban aerosols on the cloud condensation activity using a clustering model, Science of The Total Environment, Volume 858, Part 1, 2023, 159657, ISSN 0048-9697, [https://doi.org/10.1016/j.scitotenv.2022.159657]
Sponsorship
BioCloud project - MCIN/AEI RTI2018.101154.A.I00; FEDER "Unamanera de hacer Europa" European Commission 871115 ATMO_ACCESS 101008004; Ministry of Science and Innovation, Spain (MICINN) Spanish Government PID2020-12001-5RB-I00 GL2016-81092-R CGL2017-90884REDT; Junta de Andalucia; UGR; European Commission B-RNM- 474-UGR18; NIMBUS B- RNM-496UGR18; Junta de Andalucia P2000136 AEROPRE P-18-RT-3820; University of Granada Plan Propio PPVS2018-04 LS2022-1; Spanish Government FPU19/05340; Ministry of Science and Innovation, Spain (MICINN); Spanish Government PRE2019-090827Abstract
The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to
assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei
(CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN.
We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method:
(1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban
atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to
the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped
into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite
aged traffic and urban background categories are those with lower total particle number concentrations (Ntot) these
categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions
(AF) around 0.5 at 0.75%supersaturation (SS). By contrast, road traffic is an important aerosol sourcewith thehighest frequency
of occurrence (32 %) and relatively high Ntot, however, its impact in the CCN activity is very limited likely due to
lower particlemean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated
to new particle formation (NPF) events, present large Ntot with large frequency of occurrence (22%and 28%, respectively)
but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the
CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the
CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments
where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently
contributing to climate change.